Experiencing a probabilistic approach to clarify and disclose uncertainties when setting occupational exposure limits
Journal Title: International Journal of Occupational Medicine and Environmental Health - Year 2018, Vol 31, Issue 4
Abstract
Objectives: Assessment factors (AFs) are commonly used for deriving reference concentrations for chemicals. These factors take into account variabilities as well as uncertainties in the dataset, such as inter-species and intra-species variabilities or exposure duration extrapolation or extrapolation from the lowest-observed-adverse-effect level (LOAEL) to the noobserved- adverse-effect level (NOAEL). In a deterministic approach, the value of an AF is the result of a debate among experts and, often a conservative value is used as a default choice. A probabilistic framework to better take into account uncertainties and/or variability when setting occupational exposure limits (OELs) is presented and discussed in this paper. Material and methods: Each AF is considered as a random variable with a probabilistic distribution. A short literature was conducted before setting default distributions ranges and shapes for each AF commonly used. A random sampling, using Monte Carlo techniques, is then used for propagating the identified uncertainties and computing the final OEL distribution. Results: Starting from the broad default distributions obtained, experts narrow it to its most likely range, according to the scientific knowledge available for a specific chemical. Introducing distribution rather than single deterministic values allows disclosing and clarifying variability and/or uncertainties inherent to the OEL construction process. Conclusions: This probabilistic approach yields quantitative insight into both the possible range and the relative likelihood of values for model outputs. It thereby provides a better support in decision-making and improves transparency.
Authors and Affiliations
David Vernez, Sandrine Fraize-Frontier, Raymond Vincent, Stéphane Binet, Christophe Rousselle
Keywords
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- EP ID EP359551
- DOI 10.13075/ijomeh.1896.01184
- Views 106
- Downloads 0
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